Method optimization experiments

Other chromatographic systems snch as DryLab 2000 Pins from LC Resonrces (http //www.lcresources.com) incorporate aspects of method development and validation throngh simnlation software combined with actnal experiments to determine optimal operating conditions. This system is designed to generate efficient method development and method optimization experiments. Resnlts from these experiments can be nsed for the evaluation of robusmess as part of the validation for methods developed using this type of software. 

At each step of the optimization, experiments can be performed to update the kinetic model both with respect to structure and values of the kinetic parameters. The method is illustrated with the following example. 

When from initial experiments, conditions that indicate the enantioselectivity of the system towards a given enantiomer pair or towards a limited series of substances are known, one might optimize their separation. To obtain optimal conditions, the different chemometric techniques used for method optimization in classic chromatographic or electrophoretic separations can also be applied for the chiral ones. Different experimental design approaches, using both screening and response surface designs can be In Reference 331, for... 

A SST is an integral part of many analytical methods. It verifies the suitability and the efficacy of the instrument or the setup for the intended purpose of the method. SST limits for some responses are occasionally derived from the method optimization and validation results, but quite often based on the experience of the analyst. 

Microbatch can be performed either manually or automatically (Chayen et ah, 1992). It is the simplest crystallization method and therefore can be easily performed in high-throughput trials. Current robots can dispense microbatch trials down to 1 nl volumes. Depending on the type of oils used to cover the trials, this technique can be harnessed for both screening and optimization experiments. 

Several investigations addressing these issues were performed in process-optimization experiments [71]. With regard to efficient recovery and re-use of the catalyst, use of chloroform is suitable, because of the insolubility of L-proline. Although the ee obtained was somewhat lower (61% ee for (R)-38b in CHCI3 compared with 76% ee in DMSO), the organocatalyst was quantitatively recovered by simple filtration and re-use of the catalyst indicated there was no loss of activity. As an alternative method, immobilization of L-proline on a silica gel column was studied but resulted in less satisfactory results [71]. 

To design an experiment means to choose the optimal experiment design to be used simultaneously for varying all the analyzed factors. By designing an experiment one gets more precise data and more complete information on a studied phenomenon with a minimal number of experiments and the lowest possible material costs. The development of statistical methods for data analysis, combined with development of computers, has revolutionized the research and development work in all domains of human activities. 

The benefit to this unconventional approach to method validation is that many of the standard method-development experiments lend themselves to the validation. For example, the method changes that normally surround the optimization of a method provide important robustness data for the validation. 

Conjugated dehydrogenation of isopropylbenzene was planned [87] by the method of experiments with the minimal number of tests. Total yields of styrene and a-methylstyrene per injected isopropylbenzene were taken for optimized parameters, because these monomers are equally valuable. At the gradient motion (T = 640 °C) the highest yield of the target products (styrene + a-methylstyrene) equaled 56.8% with about 90% selectivity. Further gradient motion was of no practical interest due to a process selectivity decrease down to 80%. 

Section 5.2 describes simultaneous methods of optimization. In these methods all experiments are performed according to a pre-planned schedule. After all the experiments have been performed, the optimum is located. 

Another method for experiment optimization concerns the sample. Here, it is desirable to inject the sample with the lowest detectable concentration, as high... 

Thus the optimization of an FFF experiment depends greatly on the analytical demands. If a rapid separation is required, one would apply field programming with cost to resolution and precision of the measurement. For very precise measurements, on the other hand, one must consider long experimental times as well as repetitions of the experiment under partly significant differing conditions. Sometimes many problems have to be addressed before a suitable fractionation can be achieved. For a good description of such a method optimization process see [166]. 

Hie typical output from method optimization software is a resolution map, as shown in Figure 10-1. The map shows resolution of the critical pair (two closest eluting peaks) as a function of the parameter(s). The example shows resolution as a function of gradient time (slope of the gradient). The resolution map has several advantages as an experimental display tool It forms a concise summary of experiments performed, it allows the chromatographer to select areas of interest and communicate the expected result, and it facilitates the viewing of data that would allow for a more robust separation. 

All approaches to method optimization based on multiple experiments have the requirement that all components be detected and that they be tracked between runs. For complex samples, this is typically the most labor-intensive aspect of method development. For unattended method development, the instrument is required to monitor the change in retention of each component automatically. The historical limitations to this technology have been a key stumbling block in the widespread adoption of automated method development. 

Peak Matching in Method Optimization. An initial solution to the problem of peak tracking across multiple experiments was the isolation of each impurity on a preparative or semiprep scale, followed by injection of each component individually. The chromatographic world has essentially rejected this concept outright. Very few chromatographers have the time or willingness to isolate standards for each component. The use of crude samples and mother... 

S. Kdrkel, E. Kostina, H. G. Bock, J.P. Schloder, 2004, Numerical methods for optimal control problems in design of robust optimal experiments for nonlinear dynamic processes. Opt. Methods and Software, 19, 327-338. 

The method of steepest ascent determines the direction from an initial experimental domain which has the steepest slope upwards along the response surface, and hence point towards the optimum conditions. A series of experiments can then be run along this steepest ascent vector. This will lead to rapid improvements. The method was introduced by Box and Wilson[l] and was the first method for systematic multivariate optimization experiments in chemistry. 

Examination of the synthetic route used in production allows for the prediction of potential residual synthetic impurities present in the drug substance. The API structure allows for the postulation of degradation pathways via hydrolytic, oxidative, catalytic, and other mechanisms. Both of these evaluations serve to facilitate the interpretation of (subsequent) identification tests. An examination of the physicochemical properties also allows for the rational establishment of method screening experiments by precluding certain conditions. For example, the use of normal-phase HPLC will be eliminated if the API is a salt or shows limited solubility in nonpolar organic solvents. Similarly, if the API (or suspected related substances) has no significant chromophore above 250 nm, the use of tetrahydrofuran (THE) and other solvents as mobile-phase components is severely limited. For compounds with an ionizable group, variation of pH will have considerable influence on elution behavior and can be exploited to optimize the selectivity of a reversed-phase separation. 

Prior to beginning the validation activities, the following deliverables should be complete from the method development exercise and reports available (1) method robustness, (2) method optimization, (3) method specificity, (4) system suitability, (5) method procedure, and (6) preliminary validation experiments used to establish validation acceptance criteria. 

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